Triple
T7422464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Target Corporation |
E171282
|
entity |
| Predicate | brandName |
P1500
|
FINISHED |
| Object |
Threshold
Threshold is a Target-exclusive home goods brand offering stylish and affordable furniture, décor, and household essentials.
|
E664362
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Threshold | Statement: [Target Corporation, brandName, Threshold]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Threshold Context triple: [Target Corporation, brandName, Threshold]
-
A.
Threshold
Threshold is the internal codename Microsoft used during development of the Windows 10 operating system.
-
B.
Threshold
Threshold is a science fiction television series created by Brannon Braga (along with others) that explores a secret government response to an alien first-contact event.
-
C.
Trigger
Trigger was the famous golden palomino horse best known as Roy Rogers’ iconic movie and television mount in mid-20th-century Westerns.
-
D.
Trigger
Trigger is a Canadian drama film featuring Molly Parker in a leading role.
-
E.
Turning Point
"Turning Point" is a notable work associated with the Mario franchise, likely referring to a specific game, level, or narrative milestone recognized by fans or creators.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Threshold Triple: [Target Corporation, brandName, Threshold]
Generated description
Threshold is a Target-exclusive home goods brand offering stylish and affordable furniture, décor, and household essentials.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Threshold Target entity description: Threshold is a Target-exclusive home goods brand offering stylish and affordable furniture, décor, and household essentials.
-
A.
Threshold
Threshold is the internal codename Microsoft used during development of the Windows 10 operating system.
-
B.
Threshold
Threshold is a science fiction television series created by Brannon Braga (along with others) that explores a secret government response to an alien first-contact event.
-
C.
Trigger
Trigger was the famous golden palomino horse best known as Roy Rogers’ iconic movie and television mount in mid-20th-century Westerns.
-
D.
Trigger
Trigger is a Canadian drama film featuring Molly Parker in a leading role.
-
E.
Turning Point
"Turning Point" is a notable work associated with the Mario franchise, likely referring to a specific game, level, or narrative milestone recognized by fans or creators.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c68a625d048190af70eb8b63bec5a0 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f2ed29ec8190804564185fe20797 |
completed | March 27, 2026, 9:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c81effc488819086336eea92604fa8 |
completed | March 28, 2026, 6:33 p.m. |
| NEDg | Description generation | batch_69c81fe025d081909f2a5c4515c60f64 |
completed | March 28, 2026, 6:37 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c824010104819081977e89d79ebb44 |
completed | March 28, 2026, 6:54 p.m. |
Created at: March 27, 2026, 3:11 p.m.